Highly compact and cost-effective 2-beam super-resolution structured illumination microscope based on all-fiber optic components.

Current super-resolution structured illumination microscopes (SR-SIM) utilize relatively expensive electro-optic components and free-space optics, resulting in large setups. Moreover, high power laser sources are required to compensate for the losses associated with generating the illumination pattern by diffractive optics. Here, we present a highly compact and flexible 2D SR-SIM microscope based on all-fiber optic components (fiberSIM). Fiber-splitters deliver the laser light to the sample resulting in the interference illumination pattern. A microelectromechanical systems (MEMS) based fiber switch performs rapid pattern rotation. The pattern phase shift is achieved by the spatial displacement of one arm of the fiber interferometer using a piezoelectric crystal. Compared with existing methods, fiberSIM is highly compact and significantly reduces the SR-SIM component cost while achieving comparable results, thus providing a route to making SR-SIM technology accessible to even more laboratories in the life sciences.

Influence of Artificially Generated Interocular Blur Difference on Fusion Stability Under Vergence Stress.

The stability of fusion was evaluated by its breakage when interocular blur differences were presented under vergence demand to healthy subjects. We presumed that these blur differences cause suppression of the more blurred image (interocular blur suppression, IOBS), disrupt binocular fusion and suppressed eye leaves its forced vergent position. During dichoptic presentation of static grayscale images of natural scenes, the luminance contrast (mode B) or higher-spatial frequency content (mode C) or luminance contrast plus higher-spatial frequency content (mode A) were stepwise reduced in the image presented to the non-dominant eye. We studied the effect of these types of blur on fusion stability at various levels of the vergence demand. During the divergence demand, the fusion was disrupted with approximately half blur than during convergence. Various modes of blur influenced fusion differently. The mode C (isolated reduction of higher-spatial frequency content) violated fusion under the lowest vergence demand significantly more than either isolated or combined reduction of luminance contrast (mode B and A). According to our results, the image´s details (i.e. higher-spatial frequency content) protects binocular fusion from disruption by the lowest vergence demand.

Imaging tissues and cells beyond the diffraction limit with structured illumination microscopy and Bayesian image reconstruction.

Background: Structured illumination microscopy (SIM) is a family of methods in optical fluorescence microscopy that can achieve both optical sectioning and super-resolution effects. SIM is a valuable method for high-resolution imaging of fixed cells or tissues labeled with conventional fluorophores, as well as for imaging the dynamics of live cells expressing fluorescent protein constructs. In SIM, one acquires a set of images with shifting illumination patterns. This set of images is subsequently treated with image analysis algorithms to produce an image with reduced out-of-focus light (optical sectioning) and/or with improved resolution (super-resolution). Findings: Five complete, freely available SIM datasets are presented including raw and analyzed data. We report methods for image acquisition and analysis using open-source software along with examples of the resulting images when processed with different methods. We processed the data using established optical sectioning SIM and super-resolution SIM methods and with newer Bayesian restoration approaches that we are developing. Conclusions: Various methods for SIM data acquisition and processing are actively being developed, but complete raw data from SIM experiments are not typically published. Publically available, high-quality raw data with examples of processed results will aid researchers when developing new methods in SIM. Biologists will also find interest in the high-resolution images of animal tissues and cells we acquired. All of the data were processed with SIMToolbox, an open-source and freely available software solution for SIM.

Quantitative super-resolution single molecule microscopy dataset of YFP-tagged growth factor receptors.

Background: Super-resolution single molecule localization microscopy (SMLM) is a method for achieving resolution beyond the classical limit in optical microscopes (approx. 200 nm laterally). Yellow fluorescent protein (YFP) has been used for super-resolution single molecule localization microscopy, but less frequently than other fluorescent probes. Working with YFP in SMLM is a challenge because a lower number of photons are emitted per molecule compared with organic dyes, which are more commonly used. Publically available experimental data can facilitate development of new data analysis algorithms. Findings: Four complete, freely available single molecule super-resolution microscopy datasets on YFP-tagged growth factor receptors expressed in a human cell line are presented, including both raw and analyzed data. We report methods for sample preparation, for data acquisition, and for data analysis, as well as examples of the acquired images. We also analyzed the SMLM datasets using a different method: super-resolution optical fluctuation imaging (SOFI). The 2 modes of analysis offer complementary information about the sample. A fifth single molecule super-resolution microscopy dataset acquired with the dye Alexa 532 is included for comparison purposes. Conclusions: This dataset has potential for extensive reuse. Complete raw data from SMLM experiments have typically not been published. The YFP data exhibit low signal-to-noise ratios, making data analysis a challenge. These datasets will be useful to investigators developing their own algorithms for SMLM, SOFI, and related methods. The data will also be useful for researchers investigating growth factor receptors such as ErbB3.

Quality Assessment of Sharpened Images: Challenges, Methodology, and Objective Metrics.

Most of the effort in image quality assessment (QA) has been so far dedicated to the degradation of the image. However, there are also many algorithms in the image processing chain that can enhance the quality of an input image. These include procedures for contrast enhancement, deblurring, sharpening, up-sampling, denoising, transfer function compensation, etc. In this work, possible strategies for the quality assessment of sharpened images are investigated. This task is not trivial because the sharpening techniques can increase the perceived quality, as well as introduce artifacts leading to the quality drop (over-sharpening). Here, the framework specifically adapted for the quality assessment of sharpened images and objective metrics comparison in this context is introduced. However, the framework can be adopted in other quality assessment areas as well. The problem of selecting the correct procedure for subjective evaluation was addressed and a subjective test on blurred, sharpened, and over-sharpened images was performed in order to demonstrate the use of the framework. The obtained ground-truth data were used for testing the suitability of state-ofthe- art objective quality metrics for the assessment of sharpened images. The comparison was performed by novel procedure using ROC analyses which is found more appropriate for the task than standard methods. Furthermore, seven possible augmentations of the no-reference S3 metric adapted for sharpened images are proposed. The performance of the metric is significantly improved and also superior over the rest of the tested quality criteria with respect to the subjective data.

Long-Term Continuous Double Station Observation of Faint Meteor Showers.

Meteor detection and analysis is an essential topic in the field of astronomy. In this paper, a high-sensitivity and high-time-resolution imaging device for the detection of faint meteoric events is presented. The instrument is based on a fast CCD camera and an image intensifier. Two such instruments form a double-station observation network. The MAIA (Meteor Automatic Imager and Analyzer) system has been in continuous operation since 2013 and has successfully captured hundreds of meteors belonging to different meteor showers, as well as sporadic meteors. A data processing pipeline for the efficient processing and evaluation of the massive amount of video sequences is also introduced in this paper.

SIMToolbox: a MATLAB toolbox for structured illumination fluorescence microscopy.

UNLABELLED: SIMToolbox is an open-source, modular set of functions for MATLAB equipped with a user-friendly graphical interface and designed for processing two-dimensional and three-dimensional data acquired by structured illumination microscopy (SIM). Both optical sectioning and super-resolution applications are supported. The software is also capable of maximum a posteriori probability image estimation (MAP-SIM), an alternative method for reconstruction of structured illumination images. MAP-SIM can potentially reduce reconstruction artifacts, which commonly occur due to refractive index mismatch within the sample and to imperfections in the illumination. AVAILABILITY AND IMPLEMENTATION: SIMToolbox, example data and the online documentation are freely accessible at http://mmtg.fel.cvut.cz/SIMToolbox. CONTACT: ghagen@uccs.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Three-dimensional super-resolution structured illumination microscopy with maximum a posteriori probability image estimation.

We introduce and demonstrate a new high performance image reconstruction method for super-resolution structured illumination microscopy based on maximum a posteriori probability estimation (MAP-SIM). Imaging performance is demonstrated on a variety of fluorescent samples of different thickness, labeling density and noise levels. The method provides good suppression of out of focus light, improves spatial resolution, and allows reconstruction of both 2D and 3D images of cells even in the case of weak signals. The method can be used to process both optical sectioning and super-resolution structured illumination microscopy data to create high quality super-resolution images.